targets_type	autoencoder_type	batch_size
exp_id
6	Mnist	Over_dim	128
11	Mnist	normal_dim	64
20	Mnist	Over_dim_iteration	32
60	Mnist	Over_dim_tied_iteration	64
61	Mnist	Over_dim_tied_iteration	32
68	Noisy	Over_dim	64

• Batch size doesn't change the manifold significantly
• Training iteration (train the network with predictions) does influence the manifold, mostly rotation and the cluster formation it becomes slightly worse through the iterations. With Noisy data iteration (train the network with predictions) appears to change nothing.
• Tied weights also seem to make the clustering worse.
• Over_dim_tied_iteration shows in contrast to Over_dim for 10_Targets worsening. This is a combination of the worsening in Over_dim_tied and Over_dim_iteration.
• For Noisy data Over_dim and normal_dim don't present a big difference. Although normal dim produces worse reconstructions
• For Mnist data Over_dim_iteration and normal_dim_iteration don't present a big difference. Although normal dim produces worse reconstructions